Price bundling is one of the most prevalent marketing practices in many industries, including hospitality and travel. Virtually all types of firms in the hospitality and travel industry, from suppliers such as hotels and airlines to intermediaries such as travel agents, are encouraging customers to purchase travel “packages” rather than a single component of travel to save money and streamline the purchasing process. The purpose of this research is to determine whether the practice of price bundling by online travel agents results in actual monetary savings for consumers (i.e., lower prices) relative to the prices charged by individual service providers (i.e., hotels and airlines) through their own online Web sites. The results indicate that there are monetary savings in the form of lower prices realized by consumers who purchase bundled offerings from online travel agents, and there is an interaction effect between channel and hotel class.
Despite the copious anecdotal evidence available, research only recently examines the multidimensional dynamics associated with underdog brands and their essential, complex place in the business world. This research seeks to better conceptualize, operationalize, and refine the theories and constructs surrounding underdogs. The study conducts two 2 × 2 × 2 quasi-experimental between-subjects design studies to fulfill these objectives. Study 1 is designed to confirm that brand localness needs to be separated from underdog concepts as both brand cues distinctively prompt customers’ purchase activism depending on their political orientations. Study 2 extends the system justification theory by replicating Study 1 using a different context and refining control variables to better understand other potential explanations of customer behavior toward underdog/localness brand cues. The results indicate that brand positioning status and brand localness both have main effects on intent to purchase and willingness to pay a price premium. Furthermore, results find political orientation is an important moderator in determining whether customers purchase underdog brands.
The authors test an extended technology acceptance model by incorporating two situational and two attitudinal variables as new predictors of self-service technology adoption. The situational variables are waiting line and service complexity, whereas the attitudinal variables are technology trust and technology anxiety. The study employs an experimental approach with hypothetical hotel check-in situations. The authors apply structural equation modeling techniques to provide additional insights into the main effects. They find significant main effects of all situational and attitudinal variables but no interaction effects between the situational and attitudinal variables. The main effects on intention to use self-service technologies occurred primarily through the mediation of perceived ease of use and perceived usefulness. The technology acceptance model needs extension to include nontechnology variables as predictors of new technology adoption.
Special events can have a sizable economic significance (ES) and economic impact (EI) in host communities. This study's purpose was to update the input measurement concepts in assessing the EI for a short-term special event. Specific EI measurements were examined as suggested by Crompton, Lee, and Shuster (2001) and Stynes (1997) that differentiated between types of attendees. A trade market analysis (TMA) technique was applied to refine the measures of locals and nonlocals and to reconsider locals who have visiting friends and relatives (VFR) in their group profiles. Further refinement of day-trip attendees and visitors expenditure impacts were identified and used to adjust the EI when applied to a sales multiplier. Self-administered online surveys were emailed to 2,678 group leaders from a registration and on-site intercept population with a response rate of 46%. Measurement improvements were found for local, nonlocal, casual, time-switcher, and VFR attendees in EI application.
The tourism industry has come under scrutiny as a human activity that contributes to the increase in greenhouse gas (GHG) emissions. While tourism certainly contributes to GHG emissions, it would be interesting to know if the level of tourism has an effect on environmental performance. The purpose of this paper is to examine the impact of the level of tourism on GHG emissions on a global level using WDI panel data from 1995 to 2016. The findings indicate that the level of tourism does have an impact on GHG emissions. There is evidence that countries that rely more heavily on tourism as a percentage of GDP, have more tourism arrivals, and have higher tourism density actually have lower amounts of GHG emissions and better environmental performance.
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